Multivariate Analysis of Aquatic Community Data Using Ordination 2-day workshop presented by the Canadian Rivers Institute
Monday 20 March 2017 - 08:30am - Tuesday 21 March 2017 05:00pm
Course OverviewThis two-day workshop will provide an advanced look at the use of eigenanalysis-based multivariate statistics to analyze community and environmental data. Through a combination of lecture material and hands-on training conducting analysis in R, participants will gain an understanding of the use of indirect and direct gradient analysis ordination methods including principal components analysis, correspondence analysis, detrended correspondence analysis, redundancy analysis, and canonical correspondence analysis. Participants will also learn advanced methods to test and compare ordinations, including variance partitioning and Procrustes analysis. Emphasis will be placed on guiding participants through the interpretation of results to give them the tools to move forward with their own analyses.
This workshop assumes that participants have a basic understanding of the use of multivariate analysis, and it is a follow-up to the General Introduction to Multivariate Statistics workshop. Participants should come to this workshop with a basic familiarity with the use of R and RStudio (including how to load and visualize data and how to load packages).
Learning ObjectivesAt the end of this interactive 2-day workshop, participants will:
- Understand the mechanics of indirect and direct gradient analysis methods, including PCA, CA, DCA, RDA, and CCA
- Recognize the difference between unimodal and linear models of gradient analysis, understand differences in interpretation of these models, and know how to select the appropriate model for their data
- Be able to interpret ordination results and biplots for both unconstrained and constrained data
- Understand the concept and mechanics of variance partitioning to evaluate the importance of different driving variables
- Be able to compare ordinations using Procrustes analysis
University of New Brunswick
3 Bailey Drive
3 Bailey Drive
Contact Sarah Tuziak, email@example.com